How Open is Changing Research

Editor's Notes

1. Worse in some areas than others Replication crisis in psychology and biomedical science Sociology, economics, climate science also vulnerable [according to Smaldino] Poor research design and data analysis encourage false-positive findings. Such poor methods persist despite perennial calls for improvement, suggesting that they result from something more than just misunderstanding. The persistence of poor methods results partly from incentives that favour them, leading to the natural selection of bad science. This dynamic requires no conscious strategizing—no deliberate cheating nor loafing— by scientists, only that publication is a principal factor for career advancement. Some normative methods of analysis have almost certainly been selected to further publication instead of discovery. In order to improve the culture of science, a shift must be made away from correcting misunderstandings and towards rewarding understanding. We support this argument with empirical evidence and computational modelling. We first present a 60-year meta-analysis of statistical power in the behavioural sciences and show that power has not improved despite repeated demonstrations of the necessity of increasing power. To demonstrate the logical consequences of structural incentives, we then present a dynamic model of scientific communities in which competing laboratories investigate novel or previously published hypotheses using culturally transmitted research methods. As in the real world, successful labs produce more ‘progeny,’ such that their methods are more often copied and their students are more likely to start labs of their own. Selection for high output leads to poorer methods and increasingly high false discovery rates. We additionally show that replication slows but does not stop the process of methodological deterioration. Improving the quality of research requires change at the institutional level.
2. When researchers were asked how the challenges in research have influenced their careers, 65% said they had considered quitting research, and 15% that they had actually quit. Around one-third felt that they had been judged solely on the number of papers they had published, and another one-third said that they had published a paper they were not proud of. And 16% said they had cut corners in research. (Readers could choose more than one answer.)   When asked to choose the biggest challenge facing early-career scientists, 44% of some 12,000 respondents overwhelmingly picked ‘the fight for funding’. This result aligns closely with the answers of the 3,000-plus people who responded to Nature’s 2016 salary survey, just under half of whom ranked ‘competition for funding’ as the biggest challenge to their career progression. The next biggest challenges identified in the reader poll, ‘lack of work–life balance’ and ‘progression judged too heavily on publication record’ received just under one-fifth of the total vote each.
3. Slide from Danny’s talk https://docs.google.com/presentation/d/1g9eD8uANMAMTDDy0zhlytiL7MKxbYrZ6QwUBOg2Yzr8/edit?usp=sharing  Video of the presentation https://drive.google.com/drive/folders/1NY_FZ44VvtYU2rYuRhPPeSHSfhpGlZ4k The bit on rankings starts at 4.35 - 12.35 Then it goes on to "be careful what you wish for" which might be the situation we are in, in relation to the Chief Scientist at the moment.